The gap between finishing a tutorial and doing your own project is way bigger than anyone warns you about I finished a couple ML courses, went through a bunch of kaggle notebooks, thought I was making progress. then i tried building something on my own and i got humbled real quick In the courses everything just works, clean data, hit run, you get results. Then you try your own thing and you're spending days just getting the environment to not crash. Dependencies wont install, your data is in some format nothing can read, and at some point you're on stack overflow more than jupyter. The compute cost part I wasn't ready for either. I kept leaving cloud instances running while fixing stuff that wasn't even related to the mode, like I'd rent a gpu, spend 2 hours on a data loading bug, and realize the gpu was just sitting there idling while I was googling. On a student budget that gets old fast. A friend eventually told me to try hyperai cause he was tired of hearing me complain lol.…